Optimization of Robot Gripper Parameters Using Genetic Algorithms

Abstract

In this paper the multicriteria optimization model of the robot gripper is built. In this model the decision variables are geometrical dimensions of the gripper, which are under side constraints and those constraints which are yielded by the structure of the gripper. The objective functions are: (i) the difference between the maximum and minimum griping forces for the assumed range of the gripper ends displacement, (ii) the force transmission ratio between the gripper actuator and the gipper ends and (iii) the length of all the elements of the gripper. All functions are computationally expensive functions, thus a special Genetic Algorithm based multicriteria optimization method has been developed. Using this method a two-stage optimization process is proposed in which at each stage one bicriterion optimization model is solved. The presented example shows the effectiveness of the proposed approach.